Facial Emotion Analysis Implementation Using Deep Neural Networking Methods
Dr Linoy A Tharakan
, Dhiya Annie Roy
Deep Neural Networks, Emotion detection, Face recognition
One of the biggest issues for cognitive computing is figuring out how people perceive and distinguish one another's faces and emotions, as well as how to produce automated and effective face recognition. In the realm of computer science, there has been a lot of effort spent into researching ways to classify and identify faces automatically. The difficulty of recovering face traits has been approached in many ways. The crucial constraint is to create believable face representations that are robust in terms of facial feature variation. Finding faces in the scene, extracting facial features from the detected face region, and analysing the motion of facial features and/or changes in the appearance of facial features are the three subproblems that make up the problem of machine recognition of human facial expression.
"Facial Emotion Analysis Implementation Using Deep Neural Networking Methods", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 11, page no.1240 - 1242, November-2022, Available :https://ijsdr.org/papers/IJSDR2211186.pdf
Volume 7
Issue 11,
November-2022
Pages : 1240 - 1242
Paper Reg. ID: IJSDR_202761
Published Paper Id: IJSDR2211186
Downloads: 000347265
Research Area: Computer Science & Technology
Country: Ayur , Kollam, Kerala, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
